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Item 12-Lipoxygenase governs the innate immune pathogenesis of islet inflammation and autoimmune diabetes(The American Society for Clinical Investigation, 2021-07-22) Kulkarni, Abhishek; Pineros, Annie R.; Walsh, Melissa A.; Casimiro, Isabel; Ibrahim, Sara; Hernandez-Perez, Marimar; Orr, Kara S.; Glenn, Lindsey; Nadler, Jerry L.; Morris, Margaret A.; Tersey, Sarah A.; Mirmira, Raghavendra G.; Anderson, Ryan M.; Pediatrics, School of MedicineMacrophages and related myeloid cells are innate immune cells that participate in the early islet inflammation of type 1 diabetes (T1D). The enzyme 12-lipoxygenase (12-LOX) catalyzes the formation of proinflammatory eicosanoids, but its role and mechanisms in myeloid cells in the pathogenesis of islet inflammation have not been elucidated. Leveraging a model of islet inflammation in zebrafish, we show here that macrophages contribute significantly to the loss of β cells and the subsequent development of hyperglycemia. The depletion or inhibition of 12-LOX in this model resulted in reduced macrophage infiltration into islets and the preservation of β cell mass. In NOD mice, the deletion of the gene encoding 12-LOX in the myeloid lineage resulted in reduced insulitis with reductions in proinflammatory macrophages, a suppressed T cell response, preserved β cell mass, and almost complete protection from the development of T1D. 12-LOX depletion caused a defect in myeloid cell migration, a function required for immune surveillance and tissue injury responses. This effect on migration resulted from the loss of the chemokine receptor CXCR3. Transgenic expression of the gene encoding CXCR3 rescued the migratory defect in zebrafish 12-LOX morphants. Taken together, our results reveal a formative role for innate immune cells in the early pathogenesis of T1D and identify 12-LOX as an enzyme required to promote their prodiabetogenic phenotype in the context of autoimmunity.Item DeCoST: A New Approach in Drug Repurposing From Control System Theory(Frontiers, 2018-06) Nguyen, Thanh; Muhammad, Syed A.; Ibrahim, Sara; Ma, Lin; Guo, Jinlei; Bai, Baogang; Zeng, Bixin; Computer and Information Science, School of ScienceIn this paper, we propose DeCoST (Drug Repurposing from Control System Theory) framework to apply control system paradigm for drug repurposing purpose. Drug repurposing has become one of the most active areas in pharmacology since the last decade. Compared to traditional drug development, drug repurposing may provide more systematic and significantly less expensive approaches in discovering new treatments for complex diseases. Although drug repurposing techniques rapidly evolve from “one: disease-gene-drug” to “multi: gene, dru” and from “lazy guilt-by-association” to “systematic model-based pattern matching,” mathematical system and control paradigm has not been widely applied to model the system biology connectivity among drugs, genes, and diseases. In this paradigm, our DeCoST framework, which is among the earliest approaches in drug repurposing with control theory paradigm, applies biological and pharmaceutical knowledge to quantify rich connective data sources among drugs, genes, and diseases to construct disease-specific mathematical model. We use linear–quadratic regulator control technique to assess the therapeutic effect of a drug in disease-specific treatment. DeCoST framework could classify between FDA-approved drugs and rejected/withdrawn drug, which is the foundation to apply DeCoST in recommending potentially new treatment. Applying DeCoST in Breast Cancer and Bladder Cancer, we reprofiled 8 promising candidate drugs for Breast Cancer ER+ (Erbitux, Flutamide, etc.), 2 drugs for Breast Cancer ER- (Daunorubicin and Donepezil) and 10 drugs for Bladder Cancer repurposing (Zafirlukast, Tenofovir, etc.).Item DMAP: a connectivity map database to enable identification of novel drug repositioning candidates(BioMed Central, 2015-09-25) Huang, Hui; Nguyen, Thanh; Ibrahim, Sara; Shantharam, Sandeep; Yue, Zongliang; Chen, Jake Yue; Department of Computer & Information Science, School of ScienceBACKGROUND: Drug repositioning is a cost-efficient and time-saving process to drug development compared to traditional techniques. A systematic method to drug repositioning is to identify candidate drug's gene expression profiles on target disease models and determine how similar these profiles are to approved drugs. Databases such as the CMAP have been developed recently to help with systematic drug repositioning. METHODS: To overcome the limitation of connectivity maps on data coverage, we constructed a comprehensive in silico drug-protein connectivity map called DMAP, which contains directed drug-to-protein effects and effect scores. The drug-to-protein effect scores are compiled from all database entries between the drug and protein have been previously observed and provide a confidence measure on the quality of such drug-to-protein effects. RESULTS: In DMAP, we have compiled the direct effects between 24,121 PubChem Compound ID (CID), which were mapped from 289,571 chemical entities recognized from public literature, and 5,196 reviewed Uniprot proteins. DMAP compiles a total of 438,004 chemical-to-protein effect relationships. Compared to CMAP, DMAP shows an increase of 221 folds in the number of chemicals and 1.92 fold in the number of ATC codes. Furthermore, by overlapping DMAP chemicals with the approved drugs with known indications from the TTD database and literature, we obtained 982 drugs and 622 diseases; meanwhile, we only obtained 394 drugs with known indication from CMAP. To validate the feasibility of applying new DMAP for systematic drug repositioning, we compared the performance of DMAP and the well-known CMAP database on two popular computational techniques: drug-drug-similarity-based method with leave-one-out validation and Kolmogorov-Smirnov scoring based method. In drug-drug-similarity-based method, the drug repositioning prediction using DMAP achieved an Area-Under-Curve (AUC) score of 0.82, compared with that using CMAP, AUC = 0.64. For Kolmogorov-Smirnov scoring based method, with DMAP, we were able to retrieve several drug indications which could not be retrieved using CMAP. DMAP data can be queried using the existing C2MAP server or downloaded freely at: http://bio.informatics.iupui.edu/cmaps CONCLUSIONS: Reliable measurements of how drug affect disease-related proteins are critical to ongoing drug development in the genome medicine era. We demonstrated that DMAP can help drug development professionals assess drug-to-protein relationship data and improve chances of success for systematic drug repositioning efforts.Item Drug Discovery Through Drug Perturbation Pathway Modeling and Network Analysis(Office of the Vice Chancellor for Research, 2014-04-11) Ho, Tung; Hakola, Krista; Wagle, Pragat; Rouse, Evan; Shadmand, Mehdi; Han, Juyeon; Ibrahim, SaraDue to intrinsic complex molecular interactions, the “one disease – one target – one drug” strategy for disease treatment is no longer the best option to treat cancers. To assess drug pharmacological effects, we assume that “ideal” drugs for a patient can treat or prevent the disease by modulating gene expression profiles of this patient to the similar level with those in healthy people. A new approach for drug-protein interactions curation, drug-drug similarity network comparison, and integrative pathway model construction and evaluation was introduced to determine optimal drugs for various cancers. Drug-protein interaction curation is conducted to discover novel drug-protein relationships and is categorized as: up regulated, down regulated, indirect up or down, ambiguous and unknown. The manual curation can be utilized for drug repurposing and examining drug mechanism on a pathway level. A drug-drug similarity network model is built by examining similar targets, therapeutic mechanisms, side effects, and chemical structures. Drug similarity analysis is useful for drug repositioning because similar drugs may have compatible therapeutic or toxic effects for a disease. Drug similarity networks are constructed and examined through a molecular network visualization platform. An integrative disease-specific pathway model is also built to gain a more holistic view of disease mechanisms by including every significant disease-specific protein. Including drugs on the pathway through target information can also offer a clear mechanism for the drug’s action. We also transform integrated pathways into network models and ranked drugs based on the network topological features of drug targets, drug-affecting genes/proteins, and curated disease-specific proteins. Combining our three approaches could potentially lead to advances in drug repurposing and repositioning.Item Drug-drug similarity networks for anti-cancer drug discovery – Case studies on Breast Cancer, Colorectal Cancer and Leukemia(Office of the Vice Chancellor for Research, 2013-04-05) Kugbe, Selom; Grinslade, Zachary; Momoh, Salamatu; Ibrahim, SaraOver the decades, the medical industry has been challenged with the issue of producing drugs that would avoid sidetracking to other targets (off-targets) and keep away from harmful side effects (drug adverse reactions). Many researches have shown that complex diseases, such as various cancers, make the “one disease - one target - one drug” strategy unsuccessful due to the intrinsic complexity of gene-gene interactions and gene-environment interactions. In order to discover efficient treatments for these diseases, we assume that optimal drugs should be capable of down-regulating the effects of over-expressed genes while activating the under-expressed genes, when necessary, to restore the patient’s status to a healthy one. In this MURI project, we constructed drug-drug similarity network models, as two drugs having similar side effects, targets or chemical structures may have compatible therapeutic effects on the diseases. First, we retrieved a list of top-ranking drugs for specific disease (using Breast Cancer, Colorectal Cancer and Leukemia as case studies) from different data sources of connection maps, including the CMaps webserver. Second, we identified the protein targets for each drugs using databases such as PubChem, MataDor, MetaDrug, the European Bioinformaics Institute, and DrugBank. Third, we calculated similarities between two drugs by using different types of definitions based on their characteristics, such as shared targets, chemical structures, ontology and side effects. Finally, a comprehensive drug-drug similarity network with multiple similarity definitions was created for each disease, through a molecular network visualization platform - Cytoscape. These drug-drug similarity networks for specific cancer phenotypes can be applied to the validation of therapeutic effect assessment for specific anti-cancer drugs based on drug-protein networks. Our research highlights the importance of drug similarity analysis, and will eventually help anti-cancer drug discovery in silico.Item A Novel 2-Hit Zebrafish Model to Study Early Pathogenesis of Non-Alcoholic Fatty Liver Disease(MDPI, 2022-02-17) Kulkarni, Abhishek; Ibrahim, Sara; Haider, Isra; Basha, Amina; Montgomery, Emma; Ermis, Ebru; Mirmira, Raghavendra G.; Anderson, Ryan M.; Medicine, School of MedicineNonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases in adults. NAFLD progresses from benign liver fat accumulation to liver inflammation and cirrhosis, and ultimately leads to liver failure. Although several rodent models have been established for studying NAFLD, they have limitations that include cost, speed of disease development, key dissimilarities, and poor amenability to pharmacological screens. Here, we present a novel 2-hit zebrafish model to replicate aspects of NAFLD pathogenesis. We fed zebrafish larvae a high-fat diet (HFD) to drive liver fat accumulation (first hit). Next, we exacerbated liver-specific inflammation using a transgenic line (fabp10-CETI-PIC3) that induces the expression of proinflammatory cytokines following induction with doxycycline (second hit). These hits promoted fat accumulation and liver inflammation, as demonstrated by the high expression of inflammatory cytokines, macrophage infiltration, stress induction, and hepatic lipid droplet accumulation. Furthermore, zebrafish in this paradigm showed deranged glucose metabolism. To validate a small-molecule screening approach, we treated HFD-fed fish with pioglitazone, a drug shown to be beneficial for NAFLD in humans, and measured a sharp reduction in liver lipid accumulation. These results demonstrate new utility for zebrafish in modeling early NAFLD pathogenesis and demonstrate their feasibility for in vivo screening of new pharmacological interventions.Item A novel Cre-enabled tetracycline-inducible transgenic system for tissue-specific cytokine expression in the zebrafish: CETI-PIC3(The Company of Biologists, 2020-06-26) Ibrahim, Sara; Harris-Kawano, Arianna; Haider, Isra; Mirmira, Raghavendra G.; Sims, Emily K.; Anderson, Ryan M.; Pediatrics, School of MedicineMaladaptive signaling by pro-inflammatory cytokines (PICs), such as TNFα, IL1β and IFNɣ, can activate downstream signaling cascades that are implicated in the development and progression of multiple inflammatory diseases. Despite playing critical roles in pathogenesis, the availability of in vivo models in which to model tissue-specific induction of PICs is limited. To bridge this gap, we have developed a novel multi-gene expression system dubbed Cre-enabled and tetracycline-inducible transgenic system for conditional, tissue-specific expression of pro-inflammatory cytokines (CETI-PIC3). This binary transgenic system permits the stoichiometric co-expression of proteins Tumor necrosis factor a (Tnfa), Interleukin-1 beta (Il1b) and Interferon gamma (Ifng1), and H2B-GFP fluorescent reporter in a dose-dependent manner. Furthermore, cytokine misexpression is enabled only in tissue domains that can be defined by Cre recombinase expression. We have validated this system in zebrafish using an insulin:cre line. In doubly transgenic fish, quantitative real-time polymerase chain reaction demonstrated increased expression levels of tnfa, il1b and ifng1 mRNA. Moreover, specific expression in pancreatic β cells was demonstrated by both Tnfa immunofluorescence and GFP fluorescence. Cytokine-overexpressing islets elicited specific responses: β cells exhibited increased expression of genes associated with reactive oxidative species-mediated stress and endoplasmic reticulum stress, surveilling and infiltrating macrophages were increased, and β cell death was promoted. This powerful and versatile model system can be used for modeling, analysis and therapy development of diseases with an underlying inflammatory etiology.Item OR05-3 Mir-21 Contributes to Cytokine-Induced Beta Cell Dysfunction via Inhibition of mRNAs Regulating Beta Cell Identity(Oxford University Press, 2019-04-15) Ibrahim, Sara; Anderson, Ryan; Mirmira, Raghavendra; Sims, Emily; Medicine, School of MedicineA hallmark of diabetes is the loss of physical or functional β cell mass. Alterations in β cell microRNA (miRNA) profiles have been described in diabetes. MiRNAs have also been shown to serve as important regulators of β cell development and function, implicating them in β cell dysfunction during diabetes development. Our lab has previously demonstrated that β cell microRNA 21 (miR-21) is increased in models of diabetes. However, a comprehensive analysis of the β cell effects of miR-21 remain poorly defined, and the effects of miR-21 on in vivo glucose homeostasis have never been explored. To this end, we performed a comprehensive in silico analysis of bioinformatics databases to identify potential β cell targets of miR-21, which yielded multiple targets in the Transforming Growth Factor Beta 2 (Tgfb2) and Fibroblast Growth Factor Receptor 3 (Fgfr3) pathways associated with regulation of differentiation. We hypothesize that β cell miR-21 plays a critical role in inhibiting β cell function and inducing loss of β cell identity. To validate targets in vitro, we developed a model whereby miR-21 is upregulated using a dose dependent lentiviral Tetracycline-on system in INS1 cells. Overexpression of miR-21 led to a reduction in expression levels of several members of the Tgfb2 and Fgfr3 pathways as well as multiple transcription factors associated with β cell function and identity, and an increase in aldehyde dehydrogenase transcripts, consistent with β cell dedifferentiation. To verify direct interactions between miR-21 and candidate target mRNAs, a biotin pulldown experiment was performed using a 3’ biotinylated mature miR-21 construct and a 3’ biotinylated cel-miR-67 control construct. Several mRNAs associated with β cell identity were enriched in the pulldown, indicating a direct interaction with miR-21. Lineage tracing was performed within an in vivo zebrafish model of β cell specific oxidative stress in which β cells expressed a nuclear GFP signal. Whole body knock down of miR-21 by morpholino microinjection showed a protective effect in stressed β cells and rescued against a dedifferentiated phenotype. To test the effect of miR-21 on glucose tolerance in vivo, inducible β cell specific knockout (βmiR-21KO) and overexpression (βmiR-21) mice were generated by crossing Ins1tm1(CreERT2)Thor mice with miR-21 floxed mice and miR-21-CAG-Z-EGFP mice, respectively. When compared to littermate controls, intraperitoneal glucose tolerance tests (IPGTT) exhibited hyperglycemia in βmiR-21 mice and euglycemia in βmiR-21KO mice. Metabolic studies, including glucose stimulated insulin secretion (GSIS) and insulin tolerance tests (ITT) are ongoing in our mouse models. Our results implicate miR-21 as a regulator of β cell dedifferentiation during diabetes development.Item TOWARDS A PATHWAY MODELING APPROACH TO ALZHEIMER’S DISEASE DRUG DISCOVERY(Office of the Vice Chancellor for Research, 2012-04-13) Ibrahim, Sara; Capouch, Don; Chandorkar, Sujay; Chen, Jake Yue; Saykin, Andrew J.; Wu, Xiaogang; Huang, HuiNetwork pharmacology has emerged as a new topic of study in recent years. Molecular connectivity maps between drugs and genes/proteins in specific disease contexts can be particularly valuable, since the functional approach with these maps helps researchers gain global perspectives on both the therapeutic and toxicological profiles of drugs. To assess drug pharmacological effects, we assume that “ideal” drugs for a patient can treat or prevent the disease by modulating gene expression profiles of this patient to the similar level with those in healthy people. Starting from this hypothesis, we build comprehensive disease-gene-drug connectivity relationships with drug-protein directionality (inhibit/activate) information based on a computational connectivity maps (CMaps) platform. In this work, we develop a novel approach based on integrative pathway modeling. Using Alzheimer’s disease (AD) as an example, we identify and rank AD-related drugs/compounds with their overall drug-protein “connectivity map” profile. First, we retrieve AD-associated proteins through the CMaps platform by using “Alzheimer’s disease” as a query term. Second, we retrieve AD-related pathways by using those AD-associated proteins as input and searching in the Human Pathway Database (HPD) and the PubMed. Third, we integrate the AD-related pathways into unified pathway models, from which we categorize the pharmaceutical effects of candidate drugs on all AD-associated proteins as either “therapeutic” or “toxic” (Figure 1). Finally, we transform the integrated pathways into network models and rank drugs based on the network topological features of drug targets, drug-affecting genes/proteins, and curated AD-associated proteins. We demonstrate that our approach can help identify AD drug candidates with significant therapeutic potentials with small toxic side effects. The case study correlates very well with the existing pharmacology of AD drugs and highlights the significance of the CMaps platform. Ongoing studies towards this direction also have the potential of changing future process of AD drug development. 1Indiana University School of Medicine.Item TRAUMATIC BRAIN INJURY LEADS TO ABERRANT MIGRATION OF ADULT-BORN NEURONS IN THE HIPPOCAMPUS(Office of the Vice Chancellor for Research, 2012-04-13) Ibrahim, Sara; Gao, Xiang; Chen, JinhuiTraumatic brain injury (TBI) is the leading cause of death in children and young adults, leading to substantial cognitive impairment, motor dysfunction and epilepsy. There is no effective treatment for these dis-orders. The discovery of neural stem/progenitor cells (NSCs) in the adult brain raises a potentially promising strategy for repairing CNS in-jury.Our previous study showed that TBI promotes NSC proliferation in an attempt to initiate innate repair and/or plasticity mechanisms. However, the spontaneously post-traumatic recovery of hippocampal-related cognitive and memory functions is very limited. Better under-standing of neurogenesis following TBI may provide additional inter-vention to further enhance neurogenesis for successfully repairing the damaged brain following TBI. Although newborn neurons generated from NSCs are continuously added to the brain throughout our life, they must migrate from their birthplace to their appropriate destina-tion to develop into mature neurons. When we tracked the migration of newly generated neurons in the adult hippocampus after TBI, we found that a large percentage of immature neurons migrate pass their normal stopping site at the inner granular cell layer, and misplace in the outer granular cell layer of the hippocampal dentate gyrus. The aberrant migration of adult-born neurons in the hippocampus occurs 3 days after TBI, and lasts for 10 weeks, resulting in a great number of newly generated neurons misplaced in the outer granular layer in the hippocampus. The newborn neurons at the displaced position will not be able to make correct connections with their appropriate targets, and may even make wrong connections with inappropriate nearby tar-gets in the pre-existing neural network. Abnormal migration can cause several diseases including epilepsy. These results suggest that stimu-lation of endogenous adult neural stem cells following TBI might offer new avenues for cell-based therapy. Additional intervention is required to further enhance successful neurogenesis for repairing the damaged brain.